How the economy defines who wins the World Cup

Today Spain plays its final to win the Football World Cup. Beyond technical criteria, for years there have been several studies trying to establish some correlation between sport and economy. In their famous 2004 research on the Olympic Games, Who wins the Olympic Games, economists Andrew B. Bernard and Meghan R. Busse demonstrated that a nation’s total GDP — which combines the size of its population with its per capita wealth — is the best predictor of sporting success. The thesis is that money buys infrastructure, technology, and coaches, while the population provides the critical mass necessary for natural sporting talent to emerge. What do the data from this World Cup say?

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Let’s see. Since 2022, Spain has recorded an accumulated growth close to 10%, the highest among the major eurozone economies, and it is also one of the few states where the population has increased (between 2022 and 2025 it added around 1.5 million inhabitants). On the opposite front, Germany, eliminated in the round of 32, and Italy, which fell in the group stage, have had poor sporting results in a context where their demographic pyramid is aging (24-25% of the Italian population is over 65 years old, the highest proportion in the EU) and their wealth is stagnant or in recession (Germany’s accumulated GDP growth since 2022 is negative).

Also, in this edition, Morocco, Egypt, Paraguay, Colombia, Senegal, Congo, or Cape Verde challenged major football powers. “Emerging and developing economies now represent almost half of the world GDP, whereas at the beginning of the century they were around 25%, and they have contributed to most of the growth of the world economy in the last twenty years,” points out Jeremy Cunningham, from Capital Group, in his note Lessons from the biggest World Cup in history.

However, with football, several distorting factors come into play in the equation. How does it fit, for example, that a country like Argentina, winner of the last World Cup and finalist in 2026, has been one of the leaders on the field for years despite having a struggling economy?

An explanation was already suggested in 2002 by economists Robert Hoffmann, Lee Che Ging, and Bala Ramasamy in their research The socio-economic determinants of international soccer Performance for the Journal of Sports Economics, where they identified that football performance draws an inverted “U” curve with respect to GDP per capita. Their argument is that, beyond an intermediate-high wealth threshold, sporting success stagnates. The estimated inflection point was then $21,836 per capita income (at today’s exchange rate it would be almost $40,000).

Once this income level is surpassed, sporting performance tends to decline. In affluent societies, digital and academic leisure alternatives proliferate, competing for young people’s time and reducing outdoor sports practice. In contrast, in environments with greater economic inequality (measured by the Gini coefficient), as is the case of Brazil, with five World Cups, professional football remains the main social elevator. The authors speak of a “Latin factor”: through the ball, aspirations are channeled in several Latin American countries. Didn’t Diego Armando Maradona rise from the poverty of Villa Fiorito this way? In these less developed societies, thanks to lower entry barriers (it requires little equipment compared to other sports), football monopolizes attention and, moreover, children’s athletic talent is not dispersed into other disciplines.

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Another element that breaks the parallel between economic power and football power is the influence of the “star player.” In his research this year, Population, GDP per capita, and qualification for the 2026 FIFA World Cup, economist Gregory Papanikos argues that discrepancies between model predictions and actual results are due to the fortuitous and generational emergence of exceptional individual talents (such as Luka Modrić in Croatia or Cristiano Ronaldo in Portugal). “These elite players act as an exogenous human capital shock capable of raising the performance of small and low-resource teams above their demographic and economic baseline, allowing them to challenge traditional structural determinants.”

The boom of football in emerging countries also has another economic explanation: globalization. Thanks to the transfer market, a developing country does not need to have a league or millionaire local infrastructure to compete. Countries like Senegal or Morocco export their best talents to European leagues. There they train with the best technology and tactics in the world, and then “repatriate” that accumulated knowledge for free when they play with their national team.

As for China, it is true that the size of its GDP is not yet reflected on the pitch. Like in the USA, football has little cultural rooting there. But it is interesting to highlight how in the Beijing Olympics it did meet economic parameters. In the study cited at the beginning, the authors wondered how it was possible that China, until the late nineties, only achieved 6% of the medals. The answer is that subsequent public planning and massive investment in infrastructure helped to boost sporting results in an almost Keynesian way. In the end, economic models help explain why some teams start with an advantage. But they are of little use when the fate of the match is decided on a field where even God has put his hand.